1. Technical Field
The present disclosure relates to an imaging apparatus for acquiring a spectral image.
2. Description of the Related Art
A detailed physical characteristic, which has not been able to be figured out in a conventional RGB image, of an observed object can be figured out by utilizing spectrum information of a large number of bands (for example, dozens of or more bands) each of which is a narrow band. A camera which acquires this multi-wavelength information is called a “hyper spectrum camera”. Hyper spectrum cameras are utilized in various fields such as food inspection, biological examination, drug development, and component analysis of minerals.
As an application example of an image which is acquired while limiting a wavelength of an observed object to a narrow band, International Publication Ser. No. 13/002,350 discloses an apparatus which discriminates a tumor part from a non-tumor part of a subject. This apparatus detects that protoporphyrin IX which is accumulated in a cancer cell emits fluorescence of 635 nm and photo-protoporphyrin emits fluorescence of 675 nm, through irradiation of excitation light. Thus, a tumor part and a non-tumor part are discriminated from each other.
Japanese Unexamined Patent Application Publication No. 2007-108124 discloses a method for determining freshness, which is degraded with time, of a perishable food by acquiring information of reflectance characteristics of successive multi-wavelength light.
Systems of a hyper spectrum camera which is capable of measuring a multi-wavelength image or reflectance include a system utilizing compressive sensing as disclosed in a specification of U.S. Pat. No. 7,283,231, for example. An apparatus which is disclosed in the specification of U.S. Pat. No. 7,283,231 disperses light from a measurement object by a first spectral element such as a prism, then marks the light by an encoding mask, and further returns a path of a light beam by a second spectral element. Accordingly, an image which is encoded and multiplexed about a wavelength axis is acquired by a sensor. A plurality of sheets of multi-wavelength images can be reconstructed from the multiplexed image through application of compressive sensing.
Compressive sensing is a technique for reproducing more volume of data than acquired data from the acquired data of few numbers of samples. When a two-dimensional coordinate of a measurement object is (x,y) and a wavelength is denoted as λ, data f desired to be obtained is three-dimensional data of x, y, and λ. On the other hand, image data g which is obtained by a sensor is two-dimensional data which is compressed and multiplexed in a λ axis direction. Such problem that data f data volume of which is relatively larger is obtained from an acquired image g data volume of which is relatively smaller is so-called defectively-set problem and it is impossible to solve this problem in this state. However, data of a natural image generally have redundancy and this defectively-set problem can be converted into a well-set problem by taking advantage of the redundancy. Examples of a technique for reducing data volume by utilizing redundancy of an image include jpeg compression. In jpeg compression, such method is used that image information is converted into frequency components and a non-essential part of data such as a component of low visual recognition is eliminated. In compressive sensing, such technique is incorporated into arithmetic processing and a data space desired to be obtained is converted into a space which is expressed by redundancy so as to delete an unknown and obtain a solution. As this conversion, discrete cosine transform (DCT), wavelet transform, Fourier transform, total variation (TV), and the like, for example, are used.